# Autoscale

## Create

`gpu_droplets.autoscale.create(AutoscaleCreateParams**kwargs)  -> AutoscaleCreateResponse`

**post** `/v2/droplets/autoscale`

To create a new autoscale pool, send a POST request to `/v2/droplets/autoscale` setting the required attributes.

The response body will contain a JSON object with a key called `autoscale_pool` containing the standard attributes for the new autoscale pool.

### Parameters

- **config:** `Config`

  The scaling configuration for an autoscale pool, which is how the pool scales up and down (either by resource utilization or static configuration).

  - `AutoscalePoolStaticConfigParam`

  - `AutoscalePoolDynamicConfigParam`

- **droplet\_template:** `AutoscalePoolDropletTemplateParam`

- **name:** `str`

  The human-readable name of the autoscale pool. This field cannot be updated

### Returns

- `class AutoscaleCreateResponse`

  - **autoscale\_pool:** `Optional[AutoscalePool]`

### Example

```python
from gradient import Gradient

client = Gradient()
autoscale = client.gpu_droplets.autoscale.create(
    config={
        "min_instances": 1,
        "max_instances": 5,
        "target_cpu_utilization": 0.5,
        "cooldown_minutes": 10,
    },
    droplet_template={
        "name": "example.com",
        "region": "nyc3",
        "size": "c-2",
        "image": "ubuntu-20-04-x64",
        "ssh_keys": ["3b:16:e4:bf:8b:00:8b:b8:59:8c:a9:d3:f0:19:fa:45"],
        "backups": True,
        "ipv6": True,
        "monitoring": True,
        "tags": ["env:prod", "web"],
        "user_data": "#cloud-config\nruncmd:\n  - touch /test.txt\n",
        "vpc_uuid": "760e09ef-dc84-11e8-981e-3cfdfeaae000",
    },
    name="my-autoscale-pool",
)
print(autoscale.autoscale_pool)
```

## Retrieve

`gpu_droplets.autoscale.retrieve(strautoscale_pool_id)  -> AutoscaleRetrieveResponse`

**get** `/v2/droplets/autoscale/{autoscale_pool_id}`

To show information about an individual autoscale pool, send a GET request to
`/v2/droplets/autoscale/$AUTOSCALE_POOL_ID`.

### Parameters

- **autoscale\_pool\_id:** `str`

### Returns

- `class AutoscaleRetrieveResponse`

  - **autoscale\_pool:** `Optional[AutoscalePool]`

### Example

```python
from gradient import Gradient

client = Gradient()
autoscale = client.gpu_droplets.autoscale.retrieve(
    "autoscale_pool_id",
)
print(autoscale.autoscale_pool)
```

## Update

`gpu_droplets.autoscale.update(strautoscale_pool_id, AutoscaleUpdateParams**kwargs)  -> AutoscaleUpdateResponse`

**put** `/v2/droplets/autoscale/{autoscale_pool_id}`

To update the configuration of an existing autoscale pool, send a PUT request to
`/v2/droplets/autoscale/$AUTOSCALE_POOL_ID`. The request must contain a full representation
of the autoscale pool including existing attributes.

### Parameters

- **autoscale\_pool\_id:** `str`

- **config:** `Config`

  The scaling configuration for an autoscale pool, which is how the pool scales up and down (either by resource utilization or static configuration).

  - `AutoscalePoolStaticConfigParam`

  - `AutoscalePoolDynamicConfigParam`

- **droplet\_template:** `AutoscalePoolDropletTemplateParam`

- **name:** `str`

  The human-readable name of the autoscale pool. This field cannot be updated

### Returns

- `class AutoscaleUpdateResponse`

  - **autoscale\_pool:** `Optional[AutoscalePool]`

### Example

```python
from gradient import Gradient

client = Gradient()
autoscale = client.gpu_droplets.autoscale.update(
    autoscale_pool_id="0d3db13e-a604-4944-9827-7ec2642d32ac",
    config={
        "target_number_instances": 2
    },
    droplet_template={
        "name": "example.com",
        "region": "nyc3",
        "size": "c-2",
        "image": "ubuntu-20-04-x64",
        "ssh_keys": ["3b:16:e4:bf:8b:00:8b:b8:59:8c:a9:d3:f0:19:fa:45"],
        "backups": True,
        "ipv6": True,
        "monitoring": True,
        "tags": ["env:prod", "web"],
        "user_data": "#cloud-config\nruncmd:\n  - touch /test.txt\n",
        "vpc_uuid": "760e09ef-dc84-11e8-981e-3cfdfeaae000",
    },
    name="my-autoscale-pool",
)
print(autoscale.autoscale_pool)
```

## List

`gpu_droplets.autoscale.list(AutoscaleListParams**kwargs)  -> AutoscaleListResponse`

**get** `/v2/droplets/autoscale`

To list all autoscale pools in your team, send a GET request to `/v2/droplets/autoscale`.
The response body will be a JSON object with a key of `autoscale_pools` containing an array of autoscale pool objects.
These each contain the standard autoscale pool attributes.

### Parameters

- **name:** `str`

  The name of the autoscale pool

- **page:** `int`

  Which 'page' of paginated results to return.

- **per\_page:** `int`

  Number of items returned per page

### Returns

- `class AutoscaleListResponse`

  - **meta:** `MetaProperties`

    Information about the response itself.

  - **autoscale\_pools:** `Optional[List[AutoscalePool]]`

    - **id:** `str`

      A unique identifier for each autoscale pool instance. This is automatically generated upon autoscale pool creation.

    - **active\_resources\_count:** `int`

      The number of active Droplets in the autoscale pool.

    - **config:** `Config`

      The scaling configuration for an autoscale pool, which is how the pool scales up and down (either by resource utilization or static configuration).

      - `AutoscalePoolStaticConfig`

      - `AutoscalePoolDynamicConfig`

    - **created\_at:** `datetime`

      A time value given in ISO8601 combined date and time format that represents when the autoscale pool was created.

    - **droplet\_template:** `AutoscalePoolDropletTemplate`

    - **name:** `str`

      The human-readable name set for the autoscale pool.

    - **status:** `Literal["active", "deleting", "error"]`

      The current status of the autoscale pool.

      - `"active"`

      - `"deleting"`

      - `"error"`

    - **updated\_at:** `datetime`

      A time value given in ISO8601 combined date and time format that represents when the autoscale pool was last updated.

    - **current\_utilization:** `Optional[CurrentUtilization]`

  - **links:** `Optional[PageLinks]`

### Example

```python
from gradient import Gradient

client = Gradient()
autoscales = client.gpu_droplets.autoscale.list()
print(autoscales.meta)
```

## Delete

`gpu_droplets.autoscale.delete(strautoscale_pool_id)`

**delete** `/v2/droplets/autoscale/{autoscale_pool_id}`

To destroy an autoscale pool, send a DELETE request to the `/v2/droplets/autoscale/$AUTOSCALE_POOL_ID` endpoint.

A successful response will include a 202 response code and no content.

### Parameters

- **autoscale\_pool\_id:** `str`

### Example

```python
from gradient import Gradient

client = Gradient()
client.gpu_droplets.autoscale.delete(
    "autoscale_pool_id",
)
```

## Delete Dangerous

`gpu_droplets.autoscale.delete_dangerous(strautoscale_pool_id, AutoscaleDeleteDangerousParams**kwargs)`

**delete** `/v2/droplets/autoscale/{autoscale_pool_id}/dangerous`

To destroy an autoscale pool and its associated resources (Droplets),
send a DELETE request to the `/v2/droplets/autoscale/$AUTOSCALE_POOL_ID/dangerous` endpoint.

### Parameters

- **autoscale\_pool\_id:** `str`

- **x\_dangerous:** `bool`

### Example

```python
from gradient import Gradient

client = Gradient()
client.gpu_droplets.autoscale.delete_dangerous(
    autoscale_pool_id="0d3db13e-a604-4944-9827-7ec2642d32ac",
    x_dangerous=True,
)
```

## List History

`gpu_droplets.autoscale.list_history(strautoscale_pool_id, AutoscaleListHistoryParams**kwargs)  -> AutoscaleListHistoryResponse`

**get** `/v2/droplets/autoscale/{autoscale_pool_id}/history`

To list all of the scaling history events of an autoscale pool, send a GET request to `/v2/droplets/autoscale/$AUTOSCALE_POOL_ID/history`.

The response body will be a JSON object with a key of `history`. This will be
set to an array containing objects each representing a history event.

### Parameters

- **autoscale\_pool\_id:** `str`

- **page:** `int`

  Which 'page' of paginated results to return.

- **per\_page:** `int`

  Number of items returned per page

### Returns

- `class AutoscaleListHistoryResponse`

  - **meta:** `MetaProperties`

    Information about the response itself.

  - **history:** `Optional[List[History]]`

    - **created\_at:** `datetime`

      The creation time of the history event in ISO8601 combined date and time format.

    - **current\_instance\_count:** `int`

      The current number of Droplets in the autoscale pool.

    - **desired\_instance\_count:** `int`

      The target number of Droplets for the autoscale pool after the scaling event.

    - **history\_event\_id:** `str`

      The unique identifier of the history event.

    - **reason:** `Literal["CONFIGURATION_CHANGE", "SCALE_UP", "SCALE_DOWN"]`

      The reason for the scaling event.

      - `"CONFIGURATION_CHANGE"`

      - `"SCALE_UP"`

      - `"SCALE_DOWN"`

    - **status:** `Literal["in_progress", "success", "error"]`

      The status of the scaling event.

      - `"in_progress"`

      - `"success"`

      - `"error"`

    - **updated\_at:** `datetime`

      The last updated time of the history event in ISO8601 combined date and time format.

  - **links:** `Optional[PageLinks]`

### Example

```python
from gradient import Gradient

client = Gradient()
response = client.gpu_droplets.autoscale.list_history(
    autoscale_pool_id="0d3db13e-a604-4944-9827-7ec2642d32ac",
)
print(response.meta)
```

## List Members

`gpu_droplets.autoscale.list_members(strautoscale_pool_id, AutoscaleListMembersParams**kwargs)  -> AutoscaleListMembersResponse`

**get** `/v2/droplets/autoscale/{autoscale_pool_id}/members`

To list the Droplets in an autoscale pool, send a GET request to `/v2/droplets/autoscale/$AUTOSCALE_POOL_ID/members`.

The response body will be a JSON object with a key of `droplets`. This will be
set to an array containing information about each of the Droplets in the autoscale pool.

### Parameters

- **autoscale\_pool\_id:** `str`

- **page:** `int`

  Which 'page' of paginated results to return.

- **per\_page:** `int`

  Number of items returned per page

### Returns

- `class AutoscaleListMembersResponse`

  - **meta:** `MetaProperties`

    Information about the response itself.

  - **droplets:** `Optional[List[Droplet]]`

    - **created\_at:** `datetime`

      The creation time of the Droplet in ISO8601 combined date and time format.

    - **current\_utilization:** `DropletCurrentUtilization`

      - **cpu:** `Optional[float]`

        The CPU utilization average of the individual Droplet.

      - **memory:** `Optional[float]`

        The memory utilization average of the individual Droplet.

    - **droplet\_id:** `int`

      The unique identifier of the Droplet.

    - **health\_status:** `str`

      The health status of the Droplet.

    - **status:** `Literal["provisioning", "active", "deleting", "off"]`

      The power status of the Droplet.

      - `"provisioning"`

      - `"active"`

      - `"deleting"`

      - `"off"`

    - **updated\_at:** `datetime`

      The last updated time of the Droplet in ISO8601 combined date and time format.

  - **links:** `Optional[PageLinks]`

### Example

```python
from gradient import Gradient

client = Gradient()
response = client.gpu_droplets.autoscale.list_members(
    autoscale_pool_id="0d3db13e-a604-4944-9827-7ec2642d32ac",
)
print(response.meta)
```

## Domain Types

### Autoscale Pool

- `class AutoscalePool`

  - **id:** `str`

    A unique identifier for each autoscale pool instance. This is automatically generated upon autoscale pool creation.

  - **active\_resources\_count:** `int`

    The number of active Droplets in the autoscale pool.

  - **config:** `Config`

    The scaling configuration for an autoscale pool, which is how the pool scales up and down (either by resource utilization or static configuration).

    - `AutoscalePoolStaticConfig`

    - `AutoscalePoolDynamicConfig`

  - **created\_at:** `datetime`

    A time value given in ISO8601 combined date and time format that represents when the autoscale pool was created.

  - **droplet\_template:** `AutoscalePoolDropletTemplate`

  - **name:** `str`

    The human-readable name set for the autoscale pool.

  - **status:** `Literal["active", "deleting", "error"]`

    The current status of the autoscale pool.

    - `"active"`

    - `"deleting"`

    - `"error"`

  - **updated\_at:** `datetime`

    A time value given in ISO8601 combined date and time format that represents when the autoscale pool was last updated.

  - **current\_utilization:** `Optional[CurrentUtilization]`

### Autoscale Pool Droplet Template

- `class AutoscalePoolDropletTemplate`

  - **image:** `str`

    The Droplet image to be used for all Droplets in the autoscale pool. You may specify the slug or the image ID.

  - **region:** `Literal["nyc1", "nyc2", "nyc3", 11 more]`

    The datacenter in which all of the Droplets will be created.

    - `"nyc1"`

    - `"nyc2"`

    - `"nyc3"`

    - `"ams2"`

    - `"ams3"`

    - `"sfo1"`

    - `"sfo2"`

    - `"sfo3"`

    - `"sgp1"`

    - `"lon1"`

    - `"fra1"`

    - `"tor1"`

    - `"blr1"`

    - `"syd1"`

  - **size:** `str`

    The Droplet size to be used for all Droplets in the autoscale pool.

  - **ssh\_keys:** `List[str]`

    The SSH keys to be installed on the Droplets in the autoscale pool. You can either specify the key ID or the fingerprint.
    Requires `ssh_key:read` scope.

  - **ipv6:** `Optional[bool]`

    Assigns a unique IPv6 address to each of the Droplets in the autoscale pool.

  - **name:** `Optional[str]`

    The name(s) to be applied to all Droplets in the autoscale pool.

  - **project\_id:** `Optional[str]`

    The project that the Droplets in the autoscale pool will belong to.
    Requires `project:read` scope.

  - **tags:** `Optional[List[str]]`

    The tags to apply to each of the Droplets in the autoscale pool.
    Requires `tag:read` scope.

  - **user\_data:** `Optional[str]`

    A string containing user data that cloud-init consumes to configure a Droplet on first boot. User data is often a cloud-config file or Bash script. It must be plain text and may not exceed 64 KiB in size.

  - **vpc\_uuid:** `Optional[str]`

    The VPC where the Droplets in the autoscale pool will be created. The VPC must be in the region where you want to create the Droplets.
    Requires `vpc:read` scope.

  - **with\_droplet\_agent:** `Optional[bool]`

    Installs the Droplet agent. This must be set to true to monitor Droplets for resource utilization scaling.

### Autoscale Pool Dynamic Config

- `class AutoscalePoolDynamicConfig`

  - **max\_instances:** `int`

    The maximum number of Droplets in an autoscale pool.

  - **min\_instances:** `int`

    The minimum number of Droplets in an autoscale pool.

  - **cooldown\_minutes:** `Optional[int]`

    The number of minutes to wait between scaling events in an autoscale pool. Defaults to 10 minutes.

  - **target\_cpu\_utilization:** `Optional[float]`

    Target CPU utilization as a decimal.

  - **target\_memory\_utilization:** `Optional[float]`

    Target memory utilization as a decimal.

### Autoscale Pool Static Config

- `class AutoscalePoolStaticConfig`

  - **target\_number\_instances:** `int`

    Fixed number of instances in an autoscale pool.

### Current Utilization

- `class CurrentUtilization`

  - **cpu:** `Optional[float]`

    The average CPU utilization of the autoscale pool.

  - **memory:** `Optional[float]`

    The average memory utilization of the autoscale pool.